code: def test_values_devices(self) -> None:
      acqf = MockAcquisitionFunction()
      cpu = torch.device("cpu")
      cuda = torch.device("cuda")
  
      test_cases = [
          (torch.tensor([0.0], device=cpu), 1, cpu),
          ([0.0], 1, cpu),
          ([0.0, torch.tensor([0.0], device=cpu)], 2, cpu),
      ]
  
      # Can only properly test this when running CUDA tests
      if self.device == torch.cuda:
          test_cases = test_cases + [
              (torch.tensor([0.0], device=cuda), 1, cuda),
              (
                  [
                      torch.tensor([0.0], dtype=cpu),
                      torch.tensor([0.0], dtype=cuda),
                  ],
                  2,
                  cuda,
              ),
              ([0.0], 1, cpu),
              ([torch.tensor(0.0, dtype=cuda), 0.0], 2, cuda),
          ]
  
      for input, d, expected_device in test_cases:
          with self.subTest(
              input=input, d=d, expected_device=expected_device
          ):
              self.assertEqual(
                  get_device_of_sequence(input), expected_device
              )
              ff = FixedFeatureAcquisitionFunction(
                  acqf, d=d, columns=[2], values=input
              )
              self.assertEqual(ff.values.device, expected_device)
  
file_path: botorch/test/acquisition/test_fixed_feature.py
imports: import torch
  from botorch.acquisition.analytic import ExpectedImprovement
  from botorch.acquisition.fixed_feature import FixedFeatureAcquisitionFunction, get_device_of_sequence, get_dtype_of_sequence
  from botorch.acquisition.monte_carlo import qExpectedImprovement
  from botorch.models import SingleTaskGP
  from botorch.utils.testing import BotorchTestCase, MockAcquisitionFunction
label_desc: Use image node_id 3 for calling the TestFixedFeatureAcquisitionFunction obj's underlying member method code with example usage: obj.test_values_devices() without return types